דרושים » AI » Senior Detection AI Engineer

We are seeking a skilled AI/ML engineer with strong software development skills to join our dynamic team. The ideal candidate will have experience in model evaluation, improvement, and analysis, as well as hands-on experience with AI and GENAI technologies. Knowledge of AWS and GPU computing is an advantage. Experience with RAG-based projects and vision language models is a significant advantage.
Key Responsibilities
Evaluate and improve machine learning models.
Perform statistical analysis and interpret model results.
Develop and implement AI models using Python.
Utilize AWS services for model deployment and management - advantage.
Leverage GPU computing for accelerated model training and inference - advantage.
Collaborate with cross-functional teams to integrate AI solutions into products.
Stay updated with the latest advancements in AI and machine learning.

We are looking for a Cloud Threat Detections Engineer.
As a Cloud Detection Engineer, you'll be at the forefront of protecting organizations against sophisticated cloud threats, working with some of the industry's most advanced security technologies and enterprise-scale cloud environments. You'll have the unique opportunity to translate real-world adversary intelligence into innovative detection capabilities that protect many of the world's leading organizations across every major industry.
What You'll Do:
Research and develop detection content for cloud-native attacks, including identity-based threats, data exfiltration, privilege escalation, cloud-native tactics.
Create correlation logic and between runtime events and control plane activities.
Design and implement detection logic across multi-cloud and hybrid environments.
Collaborate with Threat Intelligence, OverWatch, and Incident Response teams to develop detections based on real adversary activities.
Partner with Product and Engineering teams to enhance detection capabilities.

Were looking for an exceptional Senior Cloud Security Researcher to join our growing team.
We are looking for a Cloud Security Researcher who will join our mission to revolutionize cyber defense through innovative research and cutting-edge technology. As part of our research work, you'll investigate cyberattacks targeting cloud and SaaS (Software as a Service) environments, enhancing expertise and contributing directly to the evolution of our CDR (Cloud Detection and Response) platform. Youll collaborate with cross-functional teams, bridging knowledge and aligning efforts across the organization.

What You'll Do
Lead innovative research into cyber threats targeting cloud platforms, SaaS applications, Kubernetes, and emerging technologies by leveraging state-of-the-art tools and methodologies.
Develop and refine cutting-edge detection algorithms and forensic investigation techniques to uncover and mitigate sophisticated attacks in cloud and SaaS environments.
Conduct comprehensive investigations of real-world cloud security incidents, transforming insights into actionable strategies that continually evolve our threat detection capabilities.
Share your research accomplishments and innovative findings with the security community through blog posts, conference presentations, and other professional forums, enhancing our industry reputation and fostering collaborative growth.
Contribute your expertise to shape the strategic direction and ongoing development of CDR product suite, ensuring our offerings stay ahead of evolving cyber threats.
Work closely with cross-functional teams to identify novel techniques and implement robust defenses, uniting diverse expertise to secure cloud and SaaS infrastructures.

As a Tech Leader in the AI Algorithm Engineering group, you will play a pivotal role in both managing end-to-end AI research and development efforts and hands-on involvement in key-initiatives. Your responsibility will include design, implementation, guidance and mentoring for team members, and representing the AI considerations in cross-team discussions. You will leverage your extensive experience to lead multiple AI projects, and will be a key figure in leading successful execution and in finding creative solutions to difficult bottlenecks, across data, AI, engineering and product considerations.
Responsibilities:
Lead the design, development, and implementation of accurate and robust AI algorithms for medical data with a hands-on approach.
Collaborate with cross-functional teams, including data scientists, software engineers, product managers and clinical data experts, to ensure AI considerations have a profound impact on R&D and Product decisions across the projects.
Design and conduct research and experimentation to improve algorithm performance and accuracy.
Stay at the forefront of the latest advancements in AI and machine learning, particularly in the medical domain, and drive their adoption within the team.
Oversee multiple projects, ensuring successful execution, timely delivery and alignment with product and business objectives.
Provide strategic direction and technical mentoring to elevate the capabilities of the AI team.

We are looking for a Sr. Cloud Threat Detections Engineer.
As a Senior Cloud Detection Engineer, you'll be at the forefront of protecting organizations against sophisticated cloud threats, working with some of the industry's most advanced security technologies and enterprise-scale cloud environments. You'll have the unique opportunity to translate real-world adversary intelligence into innovative detection capabilities that protect many of the world's leading organizations across every major industry.
What You'll Do:
Research and develop detection content for cloud-native attacks, including identity-based threats, data exfiltration, privilege escalation, cloud-native tactics
Create correlation logic and between runtime events and control plane activities.
Design and implement detection logic across multi-cloud and hybrid environments.
Collaborate with Threat Intelligence, OverWatch, and Incident Response teams to develop detections based on real adversary activities
Partner with Product and Engineering teams to enhance detection capabilities.

We are looking for a skilled and motivated security researcher to join our core Cyber-AI research team and help us harness the power of AI models and capabilities to solve challenges in the security domain.This role involves hands-on and multidisciplinary work, involving both cyber expertise and AI, driving novel research around LLM capabilities, limitations and developing workflow automation solutions.
Responsibilities:
Research methods & initiatives to integrate AI into cybersecurity workflows and create prototypes to prove your ideas
Apply deep Cyber domain understanding of offensive & defensive techniques to guide AI efforts and act as security expert for multidisciplinary teams
Design & create AI agents tuned for specific cybersecurity tasks, including surrounding framework and automation tools, working closely with Data Science team
Create unique training methods to keep Cyber models relevance over time
Create evaluation methods for models performance, coverage and accuracy
Stay updated with the latest advancements in AI and cybersecurity, experiment with open-source projects & tools

Our Machine Learning team is at the forefront of enabling and optimizing high-performance deep learning applications on edge devices. We are looking for a versatile and highly motivated Machine Learning Engineer with a strong R&D background to join our team.
This role requires a solid mathematical foundation, a passion for AI research, and the ability to quickly adapt to new technologies. You should feel comfortable reading and implementing academic papers while also being deeply system-orientedable to dive into hardware architecture, software toolchains, and customer applications as needed.
At our company, developing and deploying deep learning models is software-intensive, and candidates are expected to have strong programming skills in scientific computing. As an AI chip company, we highly value software-hardware integration skills, as our ultimate goal is to ensure seamless optimization for our processors.
Beyond technical expertise, we are looking for candidates who demonstrate:
Ownership and accountability taking initiative and responsibility for driving projects to completion.
Professionalism delivering high-quality work while staying up to date with the latest advancements in AI.
Teamwork collaborating effectively across teams to integrate AI solutions into real-world applications.
We encourage intellectual curiosity and a keen interest in exploring AI trends, discussing future directions, and staying informed about market developments. Candidates should enjoy working in an open, well-documented manner and be eager to present their work to peers and stakeholders.
Responsibilities
Develop and optimize Transformer-based and Generative AI models for deployment on our edge AI processors.
Stay at the forefront of Generative AI and NN computer vision research, driving innovation in edge AI applications.
Benchmark and enhance vision and generative models, ensuring seamless integration with our AI toolchain, through our Model Zoo.
Collaborate with architecture and other software teams to co-optimize models for our unique processing architecture.
Support and engage with tier-1 customers, guiding them in deploying and optimizing their AI models on our platform.

For many of us there’s that one podcast we never miss, and video content is part of our daily routine, whether it’s professional or personal. But how many of us truly understand the effort that goes on behind the scenes? Here at Riverside, we know it well. That’s exactly why we built an AI-powered platform that helps content creators, podcasters, marketeers, and more at major brands like Netflix, Disney, Google, and Microsoft to create high-quality content with ease.
Riverside’s technology streamlines the entire content creation process, turning ideas into professional-grade content with the highest production standards, without requiring expensive equipment or external services. The secret? AI-driven tools that replace traditional production roles like editing, directing, and design, automating the entire process at the click of a button.
About the Innovation Team At Riverside, the Innovation team is all about pushing the limits of AI to transform content creation. We work on everything from enhancing audio and video quality to automating production with machine learning, NLP, and computer vision. Whether it’s real-time rendering, intelligent editing, or new ways to process media, we turn cutting-edge research into practical tools that creators rely on. If you’re excited about shaping the future of media tech, you’ll fit right in.
On your day to day We are looking for a brilliant and highly motivated AI Engineer with a focus on NLP to join our team that is revolutionizing how audio and video content is transcribed, analyzed, understood, and edited. You will work closely with our product and other engineering teams, as your research and development will serve as the core of the most cutting-edge features of our mobile and web applications. You will conduct research, identify trends, and explore new methodologies to enhance the performance, efficiency, and scalability of our AI systems, while leveraging the latest tech to push the boundaries of innovation in product and bring the most value to our customers.

We are seeking a AI Lead to drive the development and deployment of intelligent applications powered by ambient IoT platform. This role will be at the forefront of building AI-native interfaces that connect the physical and digital worlds redefining how users interact with real-time data, business operations, and physical assets.

This is a flexible leadership position: Ideal for someone who can build and lead a team, or an exceptional technical expert capable of executing as a high-impact individual contributor. The role reports to the Director of Strategy and will be central to shaping AI roadmap across internal tools, customer-facing solutions, and SDKs for external developers.

Responsibilities
AI Product Execution: Lead the development of GenAI-driven products, such as intelligent agents, copilots, and self-serve interfaces for real-world sensing and IoT data.

Architecture & Engineering: Design scalable, secure, and maintainable architectures for deploying LLM-powered services in production.

AI/ML Ops & Infrastructure: Own the full lifecycle of AI solutions prompt engineering, model evaluation, vector search, function calling, monitoring, retraining.

Team Leadership (optional): Mentor and grow a team of AI engineers and applied researchers, or collaborate across squads as a senior IC.

Cross-functional Collaboration: Work with data scientists, software engineers, product managers and business stakeholders to embed generative AI into the core of data product strategy.

Customer Use Cases: Translate ambient IoT data into actionable AI experiences supporting applications in logistics, sustainability, inventory management, and supply chain visibility.

Developer Platforms: Help build the SDKs and APIs that let customers and partners create their own AI-powered workflows using technology.

Experimentation & Research: Stay at the frontier of GenAI advancements (LLMs, RAG, agents, vision-language models) and apply them to real-world constraints and data environments.

We are looking for an exceptional MLOps Team Lead to own, build, and scale the infrastructure and automation that powers state-of-the-art Large Language Models (LLMs) and AI systems.

This is a technical leadership role that blends hands-on engineering with strategic vision. You will define MLOps best practices, build high-performance ML infrastructure, and lead a world-class team working at the intersection of AI research and production-grade ML systems.

You will work closely with LLM Algorithm Researchers, ML Engineers, and Data Scientists to enable fast, scalable, and reliable ML workflows covering everything from distributed training to real-time inference optimization.

If you have deep technical expertise, thrive in high-scale AI environments, and want to lead the next generation of MLOps, we want to hear from you.

Role and Responsibilities
MLOps Infrastructure & Automation

Architect and maintain scalable, self-service ML pipelines, CI/CD workflows, and orchestration frameworks (Kubeflow, MLflow, Airflow).
Design high-scale distributed training environments, leveraging multi-GPU/TPU clusters and parallelization strategies.
Optimize ML workflows for speed, scalability, and cost efficiency across cloud (AWS/GCP) and on-prem environments.
Model Deployment & Real-Time Inference

Build ultra-low-latency, high-throughput inference architectures optimized for LLMs at scale.
Implement A/B testing, canary releases, and rollback mechanisms for model deployment.
Develop robust monitoring, logging, and alerting solutions for model performance, drift detection, and reliability.
Cloud & Compute Optimization

Lead the design and scaling of multi-cloud ML infrastructure using Kubernetes, Terraform, and ArgoCD.
Optimize GPU/TPU utilization, autoscaling, and resource allocation to maximize efficiency.
Build and manage feature stores, data pipelines, and large-scale storage solutions.
Leadership & Cross-Team Collaboration

Work closely with LLM researchers, ML engineers, and platform teams to align MLOps infrastructure with cutting-edge AI research and real-world deployment needs.
Define and enforce best practices for model governance, security, and compliance.